Impact of Real Time Feedback Features on Listening Accuracy of Chinese University English Learners via iSmart teaching Platforms

Authors

  • Min Huang Office of International Cooperation and Exchanges, Hunan University of Humanities, Science and Technology, Loudi, Hunan, 417000, China
  • Malissa Maria Mahmud School of Education, Sunway University, Selangor, 47500, Malaysia
  • Goh Chin Shuang Academy of Language Studies, Universiti Teknologi MARA, Shah Alam Selangor, 40450, Malaysia

Keywords:

real-time feedback, listening accuracy, Chinese university students, English language learning, iSmart teaching platforms, educational technology

Abstract

The use of real-time feedback devices on intelligent teaching platforms is one of the ways in which English learning is transformed, especially for Chinese university students, who have special problems in listening transmission exercises. This is a systematic literature review of studies on effectiveness of the listening accuracy among Chinese university students of English based on feedback in real time and delivered on iSmart teaching platform. The review integrates the findings from 30 papers published in peer-reviewed journals from 2021 to 2025 on technological interventions, pedagogical models, and learning results. Key outcomes of the present study are that real-time feedback systems significantly enhance listening to accuracy by the provision of immediate corrective information, offload cognitive processing via adaptive scaffolded learning pathways, and sustain learner attention by using personalized feedback loops. Three main overarching categories of feedback mechanisms are highlighted in the review: immediate corrective feedback, adaptive response systems, and multimodal feedback integration. The results show that the use of the technology-enhanced platform with real-time feedback would help students achieve 15-25% increase in listening comprehension accuracy, as opposed to traditional approaches. The study also finds that tolerance of feedback delay, personalization algorithms, and cultural fit of feedback delivery have a significant impact on the learning outcomes. Challenges that were discovered relate to infrastructure shortcomings, overdependence on machine feedback and the necessity for appropriate human-AI interaction in language learning environments. The review finds that although real-time feedback components are demonstrating potential to enhance listening to accuracy, successful integration of such components depends on adequate attention to learner factors, technological affordances, and pedagogical principles. Scope for future investigation is to examine retention over the long term, enhance feedback after scheduling, at what point to provide feedback scheduling and to develop culture fair feedback scheduling system for different sets of learners.

Author Biographies

Min Huang, Office of International Cooperation and Exchanges, Hunan University of Humanities, Science and Technology, Loudi, Hunan, 417000, China

huangmin0929@126.com 

Malissa Maria Mahmud, School of Education, Sunway University, Selangor, 47500, Malaysia

malissam@sunway.edu.my 

Goh Chin Shuang , Academy of Language Studies, Universiti Teknologi MARA, Shah Alam Selangor, 40450, Malaysia

chinshuanggoh163@163.com

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Published

2025-11-23

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Section

Articles